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Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs

Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2347526764

Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs

About this item

Full title

Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs

Publisher

Berlin/Heidelberg: Springer Berlin Heidelberg

Journal title

Graefe's archive for clinical and experimental ophthalmology, 2020-04, Vol.258 (4), p.851-867

Language

English

Formats

Publication information

Publisher

Berlin/Heidelberg: Springer Berlin Heidelberg

More information

Scope and Contents

Contents

Purpose
To develop a deep learning approach based on deep residual neural network (ResNet101) for the automated detection of glaucomatous optic neuropathy (GON) using color fundus images, understand the process by which the model makes predictions, and explore the effect of the integration of fundus images and the medical history data from patie...

Alternative Titles

Full title

Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_proquest_miscellaneous_2347526764

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_2347526764

Other Identifiers

ISSN

0721-832X

E-ISSN

1435-702X

DOI

10.1007/s00417-020-04609-8

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